A fully connected, distributed mesh feedback approach to photonic A/D conversion

Author

Shoop, Barry L. ; Das, Pradip K. ; Talty, T.J. ; Ressler, E.K.

Author_Institution

Dept. of Electr. Eng. & Comput. Sci., US Mil. Acad., West Point, NY, USA

fYear

2000

fDate

7-12 May 2000

Firstpage

491

Lastpage

492

Abstract

Summary form only given.A novel approach to photonic A/D conversion using a distributed neural network, oversampling techniques, and a smart pixel hardware implementation is described. In this approach, the input signal is first sampled at a rate higher than that required by the Nyquist criterion and then presented spatially as the input to a two-dimensional error diffusion neural network consisting of X/spl times/Y neurons, each representing a pixel in the image space. We believe we have demonstrated the first dynamic operation of a 5 x 5 CMOS-SEED smart pixel implementation of the error diffusion neural network demonstrating the applicability of this new approach to high resolution photonic A/D conversion.

Keywords

CMOS integrated circuits; Nyquist criterion; SEEDs; analogue-digital conversion; electro-optical modulation; integrated optoelectronics; semiconductor quantum wells; smart pixels; 5 x 5 CMOS-SEED smart pixel implementation; MQW modulators; Nyquist criterion; distributed neural network; dynamic operation; error diffusion neural network; fully connected distributed mesh feedback approach; high resolution photonic A/D conversion; image space; input signal; oversampling techniques; photonic A/D conversion; smart pixel hardware implementation; two-dimensional error diffusion neural network; Circuit simulation; Feedback; Filters; Image analysis; Neurofeedback; Noise reduction; Optimized production technology; Polymers; Silicon; Tires;

fLanguage

English

Publisher

ieee

Conference_Titel

Lasers and Electro-Optics, 2000. (CLEO 2000). Conference on

Conference_Location

San Francisco, CA, USA

Print_ISBN

1-55752-634-6

Type

conf

DOI

10.1109/CLEO.2000.907293

Filename

907293